Journal of Intelligent & Fuzzy Systems - Volume 39, issue 2

Authors: Gui, Xin

Article Type: Research Article

Abstract: Performance appraisal in business administration has a great impact on social and economic development, so a sound performance appraisal system should be established. Moreover, in the information age, scientific methods are needed to improve business management performance. Based on this, this study links artificial intelligence with convolutional neural networks, and builds a corresponding performance research model based on actual conditions. When building the model, this paper selects the data width of 8Bit and 32 data per line, and shifts storage 2 rows, and sets the read/write enable signal to be half of the clock signal. In addition, the image matrix …of the input image subjected to nonlinear processing by the excitation function ReLU will exhibit sparsity. Finally, combined with the model and data constructed in this study, the model is validated and the relevant strategies for performance evaluation are obtained. Show more

Keywords: Artificial intelligence, convolutional neural network, business management, performance evaluation, simulation analysis

DOI: 10.3233/JIFS-179954

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 1817-1829, 2020

Authors: Yuan, Na

Article Type: Research Article

Abstract: It is of great theoretical significance and practical value to analyze the characteristics of users and behaviors in social networks, to study the personalized recommendation algorithms of users, to explore the inherent laws of event development, and to predict the movement of information or opinions. This paper analyzes the Weibo behavior through machine learning and cloud computing technology. Moreover, this paper studies and analyzes traditional network algorithms, and proposes a microblog recommendation algorithm based on statistical features. At the same time, the research content of this paper focuses on microblog contents, user characteristics, user preferences, and influence levels. The algorithm …has simple structure and strong computing performance and performs feature data mining through cloud computing big data method, which is suitable for online mining microblog behavior. In addition, the performance of the algorithm was analyzed by design comparison experiments. The research indicates that the research algorithm proposed in this paper has certain advantages, which can be applied to network behavior analysis mining, and can provide theoretical reference for subsequent related research. Show more

Keywords: Machine learning, cloud computting, microblogging, behavior analysis, user characteristics

DOI: 10.3233/JIFS-179955

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 1831-1842, 2020

Authors: Guan, Xiaoxu | Fan, Yixuan | Qin, Qirong | Deng, Ke | Yang, Gen

Article Type: Research Article

Abstract: The transfer of scientific and technological achievements is an inevitable stage in the application of science and technology to the process of productivity. This process is accompanied by various influencing factors. How to eliminate the influence of adverse influence factors on the transformation of technology into productivity is crucial to the development of social productive forces. Based on this, from the perspective of deep learning, this study builds a technology transfer transformation platform through deep learning combined with data mining technology and analyzes the method in detail. On this basis, this paper takes a city as an example to analyze …the platform of scientific and technological achievements transfer. In addition, by collecting existing data as system input and data mining analysis, this paper summarizes the advantages, disadvantages, opportunities and threats of the city’s enterprises in the transformation of results and proposes corresponding countermeasures. The example verification shows that the method proposed in this study has certain practical effects and can provide theoretical reference for subsequent related research. Show more

Keywords: Deep learning, data mining, transfer of scientific and technological achievements, convolutional neural network, system analysis

DOI: 10.3233/JIFS-179956

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 1843-1854, 2020

Authors: Cao, Huifang

Article Type: Research Article

Abstract: At present, English teaching does not play the role of a smart classroom, and it is difficult to grasp the student status and characteristics in real time in actual teaching. Based on this, starting from the video image and static image and the actual situation of English classroom teaching, this study, based on the convolutional neural network and random forest algorithm, performs static image human behavior recognition under different image representation conditions, and studies the influence of background information of image and spatial distribution information of image features on recognition accuracy. Then, based on the similarity between different behavior classes, …a static image human body behavior recognition method based on improved random forest is proposed. In addition, through theoretical research, an algorithm model that can identify the characteristics of English classrooms is constructed, and the static and dynamic images of English teaching are taken as an example to conduct experimental analysis. The research shows that the proposed method has certain effects and can provide theoretical reference for subsequent related research. Show more

Keywords: Convolutional neural network, random forest, static image, English classroom, feature recognition

DOI: 10.3233/JIFS-179957

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 1855-1865, 2020

Authors: Xu, Nianli | Liu, Fengying

Article Type: Research Article

Abstract: The image content retrieval can effectively promote the development of the entire industry. At present, sports competition is becoming more and more fierce, and the requirements for image content retrieval are getting higher and higher. In this paper, research has been carried out on image descriptor generation, image feature quantization and coding, accurate nearest neighbor cluster center fast search, multi-dimensional inverted index construction and fast retrieval. Moreover, based on deep learning, this paper constructed an effective detection algorithm for the characteristics of sports images, and compared the image shape and color as examples. It can be seen from the comparative …study that the research method of this paper can effectively reduce the size of the candidate set of query results without affecting the accuracy of the query, which is of great significance for improving the speed of image query and has certain significance for promoting the development of sports public industry. Show more

Keywords: Deep learning, image content retrieval, feature extraction, sports industry, image feature analysis

DOI: 10.3233/JIFS-179958

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 1867-1877, 2020

Authors: Quan, Yu

Article Type: Research Article

Abstract: With the continuous development of science and technology, computer-aided teaching has become a common mode of school teaching. From the current situation, it can be seen that the current computer-aided teaching mostly replaces the traditional teaching mode with multimedia, and does not play the role of functional teaching, and teachers cannot effectively grasp the students’ psychological thoughts in teaching. Based on this, this study combines machine learning prediction and artificial intelligence KNN algorithm to actual teaching. Moreover, this study collects video and instructional images for student feature behavior recognition, and distinguishes individual features from group feature recognition, and can detect …student expression recognition in detail. In addition, this study designed a case study to analyze the performance of the algorithm. From the experimental results, it can be seen that the proposed algorithm has certain effects and can be used as an algorithm to assist the teaching process and can provide theoretical reference for subsequent related research. Show more

Keywords: Machine learning prediction, artificial intelligence, KNN algorithm, auxiliary teaching, feature recognition

DOI: 10.3233/JIFS-179959

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 1879-1890, 2020

Authors: Li, Pengpeng | Jiang, Shuai

Article Type: Research Article

Abstract: If there are more external interference factors in the process of intelligent recognition in English, the recognition accuracy will be greatly reduced. It is of great academic value and application significance to deeply study feature recognition of English part-of-speech and realize automatic image processing of English recognition. Based on unsupervised machine learning and image recognition technology, this study combines the actual factors of English recognition to set the corresponding influencing factors and proposes a reliable method to identify multi-body rotating characters. This method utilizes the principle of the periodic characteristics of the trajectory rotation on the feature space. Moreover, this …study conducts a comparative analysis of recognition accuracy by comparative experiments. In addition, this paper analyzes the recognition principles of 4 fonts in detail. The research results show that the proposed method has certain effects and can provide theoretical reference for subsequent related research. Show more

Keywords: Unsupervised learning, image recognition, feature recognition, English recognition, characteristic analysis

DOI: 10.3233/JIFS-179960

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 1891-1901, 2020

Authors: Yu, Jing

Article Type: Research Article

Abstract: Task degree has become one of the important indicators to measure students’ English learning intensity and learning quality, and the difference in task degree has different effects on students’ English learning. In order to realize the task recognition of English classroom teaching, combined with the characteristics of deep learning, this study combines the actual situation of English classroom teaching to analyze, and distinguishes characters through student positioning and feature recognition. Moreover, this paper combines the characteristics of English learning scoring to judge students’ learning situation, and designs a shallow convolutional neural network based on TensorFlow architecture for identifying images and …uses GPU training acceleration to solve the problem of training time-consuming in the face of large data volume. In addition, the task results feedback is evaluated by scoring method, and the performance of the algorithm is analyzed by experiments. By setting the category of sensitive targets, this paper can perceive the results according to the target location and mark the sensitive targets in the input scene image. The research results show that the method proposed in this paper has certain effects. Show more

Keywords: Deep learning, task degree, learning feature recognition, english classroom, score

DOI: 10.3233/JIFS-179961

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 1903-1914, 2020

Authors: Wu, Wentie | Xu, Shengchao

Article Type: Research Article

Abstract: The rise of the cloud computing model has resulted in more than terabytes of data being stored in the cloud platform every day on the Internet. Mining valuable information from these massive data has become an emerging industry direction, but the current Intrusion-detection system (IDS) has been unable to adapt to large-scale log information mining. Therefore, an association rule mining algorithm based on MapReduce parallel computing framework is proposed. Firstly, the frequent itemsets mining algorithm Apriori is analyzed, and the MapReduce model is used to parallelize and improve it to more efficiently complete the mining of frequent itemsets. Secondly, the …parallel Apriori is designed to run on IDS. Finally, the simulation experiment was carried out by building an open source cloud computing framework Hadoop cluster. Finally, the simulation experiment was carried out by building an open source cloud computing framework Hadoop cluster. The results show that the proposed method has higher detection efficiency when processing massive data, and requires less processing time. Show more

Keywords: Cloud computing, intrusion detection, association rule data mining, Apriori, Hadoop, MapReduce, parallelization

DOI: 10.3233/JIFS-179962

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 1915-1923, 2020

Authors: Yang, Ningning | Dey, Nilanjan | Sherratt, R. Simon | Shi, Fuqian

Article Type: Research Article

Abstract: Speech Emotion Recognition (SER) has been widely used in many fields, such as smart home assistants commonly found in the market. Smart home assistants that could detect the user’s emotion would improve the communication between a user and the assistant enabling the assistant to offer more productive feedback. Thus, the aim of this work is to analyze emotional states in speech and propose a suitable algorithm considering performance verses complexity for deployment in smart home devices. The four emotional speech sets were selected from the Berlin Emotional Database (EMO-DB) as experimental data, 26 MFCC features were extracted from each type …of emotional speech to identify the emotions of happiness, anger, sadness and neutrality. Then, speaker-independent experiments for our Speech emotion Recognition (SER) were conducted by using the Back Propagation Neural Network (BPNN), Extreme Learning Machine (ELM), Probabilistic Neural Network (PNN) and Support Vector Machine (SVM). Synthesizing the recognition accuracy and processing time, this work shows that the performance of SVM was the best among the four methods as a good candidate to be deployed for SER in smart home devices. SVM achieved an overall accuracy of 92.4% while offering low computational requirements when training and testing. We conclude that the MFCC features and the SVM classification models used in speaker-independent experiments are highly effective in the automatic prediction of emotion. Show more

Keywords: Emotion recognition, back propagation neural network, extreme learning machine, Mel-frequency cepstral coefficients, smart home, support vector machine

DOI: 10.3233/JIFS-179963

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 1925-1936, 2020